code: def test_label_studio_predictions_visualization():
      """Test creation of LabelStudioImageClassificationInput and Datamodule from images."""
      download_data(
          "https://label-studio-testdata.s3.us-east-2.amazonaws.com/lightning-flash/data.zip"
      )
  
      datamodule = ImageClassificationData.from_labelstudio(
          train_export_json="data/project.json",
          train_data_folder="data/upload/",
          test_export_json="data/project.json",
          test_data_folder="data/upload/",
          val_split=0.5,
          batch_size=1,
      )
      assert datamodule
      app = launch_app(datamodule)
      predictions = [[0, 1], [1, 0]]
      vis_predictions = app.show_predictions(predictions)
      assert len(vis_predictions) == 4
      assert (
          vis_predictions[0]["result"][0]["id"]
          != vis_predictions[3]["result"][0]["id"]
      )
      assert (
          vis_predictions[1]["result"][0]["id"]
          != vis_predictions[2]["result"][0]["id"]
      )
      tasks_predictions = app.show_tasks(predictions)
      assert len(tasks_predictions) == 4
      tasks_predictions_json = app.show_tasks(
          predictions, export_json="data/project.json"
      )
      assert tasks_predictions_json
  
file_path: lightning-flash/tests/core/integrations/labelstudio/test_labelstudio.py
imports: import pytest
  from flash.core.data.utils import download_data
  from flash.core.integrations.labelstudio.input import LabelStudioImageClassificationInput, LabelStudioInput, LabelStudioTextClassificationInput, _load_json_data
  from flash.core.integrations.labelstudio.visualizer import launch_app
  from flash.core.utilities.imports import _TOPIC_CORE_AVAILABLE, _TOPIC_IMAGE_AVAILABLE, _TOPIC_TEXT_AVAILABLE, _TOPIC_VIDEO_AVAILABLE
  from flash.core.utilities.stages import RunningStage
  from flash.image.classification.data import ImageClassificationData
  from flash.text.classification.data import TextClassificationData
  from flash.video.classification.data import LabelStudioVideoClassificationInput, VideoClassificationData
label_desc: Use image node_id 5 for calling a global function with example usage: test_label_studio_predictions_visualization() without return types